We also explored how models trained on SpaceNet MVOI performed on building footprint extraction from imagery from other geographies, in this case, the Las Vegas imagery from SpaceNet [1]}. After normalizing the Las Vegas (LV) imagery for consistent pixel intensities and channel order with SpaceNet MVOI, we predicted building footprints in LV imagery and scored prediction quality as described in Metrics. We also re-trained TernausNet on the LV imagery and examined building footprint extraction quality on the SpaceNet MVOI test set. Strikingly, neither model was able to identify building footprints in the unseen geographies, highlighting that adding novel looks angles does not necessarily enable generalization to new geographic areas.
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